Literature DB >> 23005178

Locating privileged spreaders on an online social network.

Javier Borge-Holthoefer1, Alejandro Rivero, Yamir Moreno.   

Abstract

Social media have provided plentiful evidence of their capacity for information diffusion. Fads and rumors but also social unrest and riots travel fast and affect large fractions of the population participating in online social networks (OSNs). This has spurred much research regarding the mechanisms that underlie social contagion, and also who (if any) can unleash system-wide information dissemination. Access to real data, both regarding topology--the network of friendships--and dynamics--the actual way in which OSNs users interact, is crucial to decipher how the former facilitates the latter's success, understood as efficiency in information spreading. With the quantitative analysis that stems from complex network theory, we discuss who (and why) has privileged spreading capabilities when it comes to information diffusion. This is done considering the evolution of an episode of political protest which took place in Spain, spanning one month in 2011.

Mesh:

Year:  2012        PMID: 23005178     DOI: 10.1103/PhysRevE.85.066123

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  12 in total

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5.  Dynamical signatures of collective quality grading in a social activity: attendance to motion pictures.

Authors:  Juan V Escobar; Didier Sornette
Journal:  PLoS One       Date:  2015-01-22       Impact factor: 3.240

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7.  Core-like groups result in invalidation of identifying super-spreader by k-shell decomposition.

Authors:  Ying Liu; Ming Tang; Tao Zhou
Journal:  Sci Rep       Date:  2015-05-06       Impact factor: 4.379

8.  Dynamic-Sensitive centrality of nodes in temporal networks.

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9.  Measuring and modeling behavioral decision dynamics in collective evacuation.

Authors:  Jean M Carlson; David L Alderson; Sean P Stromberg; Danielle S Bassett; Emily M Craparo; Francisco Guiterrez-Villarreal; Thomas Otani
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10.  Locating influential nodes in complex networks.

Authors:  Fragkiskos D Malliaros; Maria-Evgenia G Rossi; Michalis Vazirgiannis
Journal:  Sci Rep       Date:  2016-01-18       Impact factor: 4.379

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